Discovering the XGBoost Boosted Tree classification model
In this section, we'll learn what the XGBoost Boosted Trees classification model is, and we'll understand which classification use cases can be tackled with this ML algorithm.
XGBoost is an open source library that provides a portable gradient boosting framework for different languages. The XGBoost library is available for different programming languages such as C++, Java, Python, R, and Scala, and can work on different operating systems. XGBoost is used to deal with supervised learning use cases, where we use labeled training data to predict target variables.
XGBoost's popularity has grown in the ML community over the years because it has often been the choice of many winning teams during ML competitions, such as the Kaggle - High Energy Physics meets Machine Learning award in 2016.
The classification capabilities of XGBoost Boosted Trees are based on the usage of multiple decision trees that classify...
